Attentional capture by spoken language: Effects on netballers’
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visual task performance 2
January 16, 2020 3
Word count (not incl. abstract, references, tables, figures & captions): 5,507
4
Abstract 1
In two experiments, participants performed visual detection, visual discrimination and 2
decision-making tasks in which a binary (left/right) response was required. In all experimental 3
conditions, a spoken word (“left”/“right”) was presented monaurally (left or right ear) at the 4
onset of the visual stimulus. In Experiment 1, 26 non-athletes located a target amongst an array 5
of distracters as quickly as possible, in both the presence and absence of spoken cues.
6
Participants performed superiorly in the presence of valid cues, relative to invalid-cue and 7
control conditions. In Experiment 2, 42 skilled netballers completed three tasks, in randomized 8
order: a visual detection task, a visual discrimination task and a netball decision-making task – 9
all in the presence of spoken cues. Our data showed that spoken auditory cues affected not only 10
target detection, but also performance on more complex decision-making tasks: cues that were 11
either spatially or semantically invalid slowed target detection time; spatially invalid cues 12
impaired discrimination task accuracy; and cues that were either spatially or semantically valid 13
improved accuracy and speeded decision time in the netball task. When studying visual 14
perception and attention in sport, the impact of concomitant auditory information should be taken 15
into account in order to achieve a more representative task design.
16
Keywords: auditory, crossmodal, decision-making, spatial attention, sport.
17
18
1. Introduction 1
Athletes are able to allocate their visual attention highly effectively (Gegenfurtner, 2
Lehtinen, & Säljö, 2011; Mann, Williams, Ward, & Janelle, 2007); and evidence suggests that 3
this improves considerably with domain-specific practice (e.g., Castiello & Umiltà, 1992; Enns 4
& Richards, 1997; Lum, Enns, & Pratt, 2002; Nougier, Ripoll, & Stein, 1989; Nougier & Rossi, 5
1999). However, attention can easily be captured by an unanticipated event in all sensory 6
modalities, even when the event is not relevant to an ongoing primary task. Whether this is a 7
bang, a tap on the shoulder, or a flash of light, we reflexively orient our attention to the perceived 8
location of the event; this is referred to as exogenous orienting of attention (see Wright & Ward, 9
2008). Our attention can also be oriented voluntarily, or endogenously; for example, when an 10
external cue is deemed relevant to the task at hand.
11
In the visual domain, the capture of attention has historically been studied using Posner’s 12
cueing paradigm (see Posner, 1980; Posner, Snyder, & Davidson, 1980), in which a cue is either 13
predictive or non-predictive (i.e., occurring at chance probability) of a subsequent target’s 14
location. When presented with exogenous cues (e.g., a briefly presented object in the same 15
hemifield as the ensuing target), people consistently respond more quickly and accurately to 16
validly cued targets, even when the possible cue locations are equiprobable (Jonides, 1981;
17
Yantis & Jonides, 1990). Posner’s (1980) paradigm has been used to investigate the effect of 18
visual cueing in sport contexts. Nougier, Ripoll, and Stein (1989) examined expert and non- 19
expert athletes’ ability to respond to cued and uncued targets presented at varying degrees of 20
eccentricity from central fixation. Not only were the experts quicker to detect more distal targets, 21
but their performance was less dependent on the validity of the cues – which implies an 22
imperviousness to such exogenous attentional orienting. Cañal-Bruland and Hagemvann (2007)
23
used a target detection task overlaid on static images of open play in soccer; participants’ aim 1
was to identify the side of the visual display in which a target black box was located. When a cue 2
(a red ellipse) was presented to the same side as the target with a 200 ms stimulus onset 3
synchrony (SOA), response times were significantly reduced when compared to those for invalid 4
contralateral cues.
5
There is also evidence to suggest that valid/predictive visual cues may actually disrupt 6
perceptual-cognitive performance. Using a 1-on-1 in soccer scenario, Cañal-Bruland (2009) 7
devised an anticipation task wherein participants’ attention was cued to regions of the opponent’s 8
body using red ellipses, immediately prior to presentation of still images. The participants’ task 9
was to decide whether the oncoming player was moving to the left or right. The cues failed to 10
direct participants’ attention successfully; in fact, response times in a no-cue control condition 11
were faster. In a second, more complex task (a 3-on-2 scenario), Cañal-Bruland noted that 12
peripheral cues speeded up response times relative to centrally-presented cues; this may reflect 13
the reflexive, automatic nature of exogenous attentional capture (Theeuwes, Kramer, Hahn, &
14
Irwin, 1998). In a third experiment, black boxes were superimposed on static images.
15
Unsurprisingly, valid cues (i.e., those appearing at the target location) speeded target detection – 16
but this did not facilitate participants’ decision-making.
17
Although research on the exogenous capture of attention has typically focused on visual 18
cues, the attention-capturing properties of auditory stimuli have recently come to prominence 19
(e.g., Koelewijn, Bronkhorst, & Theeuwes, 2009a; Sosa, Clarke, & McCourt, 2011; Spence &
20
Santangelo, 2009). Spatially non-predictive auditory cues are able to exogenously capture a 21
person’s spatial attention equally effectively as visual cues; responses to cued targets are 22
typically faster than to those at uncued locations (Wright & Ward, 2008). However, the ability of
23
any given cue, irrespective of modality, to capture an individual’s attention is partly determined 1
by the demands on attention required by competing stimuli. For example, Santangelo, Olivetti 2
Belardinelli, and Spence (2007) showed that, when participants were engaged in a perceptually 3
demanding dual-task condition that required endogenous control of attention (a rapid serial 4
visual presentation task and an orthogonal cueing task), reflexive orienting did not occur in 5
response to an extraneous auditory cue. This suggests that, when focusing one’s attention on a 6
perceptually demanding task, such as those encountered in many sporting contexts, the ability of 7
exogenous cues to distract is diminished (cf. Lavie, Hirst, de Fockert, & Viding, 2004). Visual 8
and auditory stimuli appear to compete directly with one another for our attention, in a bottom- 9
up fashion.
10
Soto and Humphreys (2007) conducted two experiments in which they examined the 11
impact of visual and verbal primes on participants’ visual attention. Participants were shown 12
shape primes 500 ms prior to conducting a visual search for a target, which was located in one of 13
four shapes within an array. The primed shape never contained the target and so visual search 14
was always impaired in the priming condition relative to a neutral one. The authors showed that 15
this effect could also be replicated with primes that comprised only a verbal description of a 16
shape; hence, they concluded that working memory (WM) of verbal information was able to bias 17
participants’ visual attention. Salverda and Altmann (2011) examined this notion further by 18
investigating the effects of spoken cues on target detection performance. In two experiments, 19
participants had to generate a saccade to the target, after hearing a word that referred to the target 20
object or to a distracter. Saccade latencies were longer when spoken cues referred to distracter 21
objects and shorter when they referred to the target, suggesting that auditory cues are also held in 22
WM during visual task performance. In a third experiment, the authors showed that participants
23
were quicker at detecting a subtle change in a target stimulus when that target had been verbally 1
cued 400 ms beforehand. It is clear from these studies that both valid and invalid verbal cues 2
directly affect visual attention processes.
3
In recent years, there has been a call for more accurate representation of the real world in 4
sport-related experimental tasks (Dicks, Davids, & Button, 2009; Pinder, Davids, Renshaw, &
5
Araújo, 2011; Vilar, Araújo, Davids, & Renshaw, 2012). In netball (as in many team sports) 6
auditory demands on a player’s attentional resources are pervasive: players gesticulate for the 7
attention of the team mate in possession of the ball, while simultaneously calling out – amidst a 8
melange of shouts and gesticulations from other team mates and opponents – yet studies of 9
visual perception and attention in sport typically examine these phenomena in a wholly 10
unrepresentative ‘auditory vacuum’. So to address this, we sought to examine the impact of 11
spoken language on participants’ visual task performance. Accordingly, two experiments were 12
devised to assess the capacity of spoken cues that varied not only spatially (ear of presentation), 13
but also semantically (“left” vs. “right”), to orient participants’ attention and ultimately affect 14
their decision-making.
15
In a pilot experiment to test the efficacy of the protocol, a group of non-athletes 16
undertook a visual detection task, wherein a target was to be detected from an array of 17
distractors; spoken cues were presented in all experimental trials.We hypothesized that valid 18
cues would reduce detection times relative to control and invalid cue conditions, consistent with 19
findings from other studies in which auditory cues were used (e.g., Salverda & Altmann, 2011).
20
Despite skilled team sport players’ ability to allocate visual attention highly effectively (Enns &
21
Richards, 1997; Nougier, et al., 1989), we predicted that skilled netballers would be prone to 22
auditory attentional capture effects – consistent with the notion that skilled team sport athletes do
23
not differ from non-athletes on fundamental measures of perception and attention (Abernethy, 1
Neal, & Koning, 1994; Hughes, Blundell, & Walters, 1993; Ward, Williams, & Loran, 2000;
2
Williams & Grant, 1999).
3
For a perceptually demanding visual discrimination task, in which judgments of 4
horizontal separation were required, we hypothesized that the task demands would attenuate 5
auditory cueing effects (cf. Koelewijn, et al., 2009b; Santangelo, et al., 2007). However, because 6
decision uncertainty was also likely to be high for this task (see Methods), we hypothesized that 7
participants would be less accurate when a semantically invalid cue was presented, because the 8
word (e.g., “left”) would increase attention to the cued side (cf. Soto & Humphreys, 2007).
9
Finally, skilled netballers undertook a netball decision-making task comprising still images taken 10
from scenarios during a competitive netball training session. We predicted that both spatially 11
invalid and semantically invalid cues would increase decision-making times, but that this effect 12
would be greatest for spatial cues, whose effects unfold rapidly (Berger, Henik, & Rafal, 2005;
13
Theeuwes, et al., 1998).
14
2. Ethics Statement 15
Prior to their participation, participants were informed, in writing and verbally, as to what was 16
required of them; they then gave their informed consent. All experimental procedures were 17
conducted pursuant to institutional ethics committee approval.
18
3.Experiment 1: Pilot Study 19
3.1. Methods 20
This pilot study was run to establish whether monaurally-presented valid and invalid 21
spoken cues had an effect on visual task performance, relative to a control condition in which 22
auditory cues were absent.
23
3.1.1. Participants.
1
Twenty-six non-netballers aged 24 to 47 years (M = 37.5 yrs; SD = 5.4 yrs) were invited 2
to take part in this pilot study. All participants had normal or corrected-to-normal vision and 3
normal hearing. All but three of the participants were right-handed.
4
3.1.2. Materials.
5
The experiment was administered on a Windows laptop computer running the E-Prime 6
software program (Psychology Software Tools, Sharpsburg, PA). The images were displayed on 7
a 15-in. display (60 Hz refresh rate). Screen resolution was set to 1024 x 768 pixels, such that the 8
images filled the screen. Participants were seated approximately 0.3 m from the laptop screen;
9
the laptop was elevated such that the centre of the screen was in line with the participant’s eye 10
level. Responses were made via two keys (numbers 3 [left] and 6 [right]) on a standard USB 11
numeric keypad, using the index and middle fingers of the right hand, respectively. The keypad 12
was positioned such that the two keys retained their original orientation - aligned in the sagittal 13
plane – to mitigate stimulus response compatibility effects (i.e., the Simon Effect; Simon &
14
Rudell, 1967; Simon & Wolf, 1963); in other words, the responses were neither left- nor right- 15
located, and so could not be described as being compatible or incompatible with the target.
16 17
3.1.2.1. Visual stimuli.
18
Participants’ aim was to identify the hemifield location of a target amongst an array of 19
distracters; Figure 1 shows a typical array (target in right hemifield; row 3, column 5). There 20
were 216 stimuli in total. All displays contained vertical black bars (no pixels lit) presented on a 21
medium grey background (one out of two pixels lit) presented on a 22
medium grey background (one out of two pixels lit). For each trial, the target item was located in 23
each of 24 possible array positions for 3 trials, totalling 72 trials in each block. The distance
24
between items was approximately 6.8° of visual angle. For every display type, the target item 1
was a vertical black bar spanning approximately 0.6° x 4.4°. The characteristic that differentiated 2
the target from the distracter items was its length: distracters were two-thirds of the length of the 3
target (2.93° approx.). Target and distracter items were jittered (deliberately misaligned) across 4
rows and columns so that the larger target did not ‘pop out’ of the array.
5
3.1.2.2. Auditory stimuli.
6
In the two experimental conditions, participants heard a brief abrupt-onset auditory cue – 7
a call of either “left” or “right” – that was presented in the corresponding ear at approximately 85 8
dBA in synchrony with the onset of the visual stimulus (Stimulus Onset Asynchrony [SOA] of 0 9
ms). For all experimental trials, there was an equal number of trials (n = 72) for which (a) both 10
the semantic and spatial components of the cues were valid (i.e., both aimed at orienting 11
attention to the half of the display containing the target; valid–valid) and (b) both components 12
were invalid (invalid-invalid); in this regard, they were non-predictive (NB: participants were 13
unaware of the predictive validity of the cues). Control trials (n = 72) were not accompanied by 14
an auditory cue.
15
3.1.3. Procedure.
16
Participants performed ten familiarisation trials; all participants reported that they 17
understood the requirements of the task. They subsequently performed a total of 216 randomized 18
experimental trials, in two blocks (n trials = 72). Participants were required to wear earphones 19
throughout the entire protocol. They were verbally informed that each trial would commence as 20
soon as the stimulus appeared and that the auditory cue may or may not relate to the correct 21
response; on-screen instructions reaffirmed this. Each trial was preceded by a fixation cross in
22
the centre of the screen for 500 ms. Displays remained visible until participants made a key press 1
response. No feedback was given in between trials. All trials were randomized.
2
3.1.4. Data analysis.
3
All data were analysed using PASW Statistics (v 18.0, SPSS Inc., Chicago, IL). A one- 4
way MANOVA (Conditions: invalid, valid, control) was performed; the dependent measures 5
were accuracy and response time.
6
3.2. Results 7
There was a main effect of Condition, F(3,23) = 11.16, P < 0.001, Pillai’s Trace = 0.59, η2p = 8
0.59. Univariate tests revealed that task accuracy was unaffected (P > 0.05), but there was an 9
effect on response time, F(2,50) = 24.12, P < 0.001, η2p = 0.49. Bonferroni-corrected pairwise 10
comparisons showed that the valid cue combination ( x = 902.79 ms, s = 299.70 ms) elicited 11
faster response times than did both invalid cues ( x = 949.40 ms, s = 307.05 ms), P < 0.001, 95%
12
CI of the difference = 22.64–70.60 ms, and the control condition ( x = 927.62 ms, s = 302.32 13
ms), P = 0.001, 95% CI of the difference = 13.02–36.66 ms. Invalid cues also elicited slower 14
response times than did the control condition, P = 0.001, 95% CI of the difference = 8.51–35.05 15
ms.
16
4. Experiment 2 17
4.1. Methods 18
4.1.1. Participants.
19
Forty-two female netball players aged 18 to 29 years (M = 21.2 yrs; SD = 3.2 yrs) were 20
recruited to take part. Their competitive experience ranged from 4 to 15 years (M = 10.5 yrs; SD 21
= 3.2 yrs); competitive standard ranged from university to international level. Participants were 22
recruited from UK university netball teams and an international netball squad. All participants
23
had normal or corrected-to-normal vision and normal hearing. All but one of the participants 1
were right-handed.
2
4.1.2. Materials.
3
All tasks were administered on a Windows computer running the E-Prime software 4
program (Psychology Software Tools, Sharpsburg, PA). The images were displayed on a 21-in.
5
display CRT monitor (75 Hz). Screen resolution was set to 1024 x 768 pixels, such that the 6
images filled the screen. Viewing distance was approximately 0.5 m. Responses were made via 7
two keys (numbers 3 and 6) on the numeric keypad of a standard keyboard, using the index and 8
middle fingers of the right hand respectively, such that the two keys were aligned in the sagittal 9
plane.
10
4.1.2.1. Visual detection task stimuli. Participants completed a visual task identical to 11
that undertaken in Experiment 1.
12
4.1.2.2. Visual discrimination task stimuli. The main aim of netball is to score more 13
goals than one’s opponents. This is typically achieved by passing the ball between team mates, 14
finally passing to a designated shooter whose aim it is to land the ball in the opponent’s hoop.
15
The outcome of any given pass may be determined, in part, by the proximity of an opponent to 16
one’s teammates, because closeness increases the likelihood that the opponent will make a 17
successful interception; hence, the perceived distance between team mates and opponents is a 18
consideration for the passer – be it an implicit or explicit one. Accordingly, in an artificial and 19
simplified version of this real-world perceptual requirement, participants were required to judge 20
the best passing option of two ‘teammates’ (light grey tunics in Figure 2) according to their 21
lateral distance from the vertical meridian – and therefore perceived distance from the 22
passer/participant; one of the two ‘team mates’ was always nearer to the vertical meridian than
23
the other. The relations between the team mates and the marking opponents (darker tunics) did 1
not vary from one stimulus to the next and so the best passing option could only be distinguished 2
by lateral distance alone. Distance from the vertical meridian was manipulated pre- 3
experimentally such that participants would typically be able to identify the best passing option 4
at above-chance levels, but without high levels of confidence in their decision: These distances 5
were derived according to the ratios used by Masters, van der Kamp, and Jackson (2007) in their 6
examination of judgments in soccer penalty-taking, so as to maximise the perceptual challenge of 7
the task. Figure 2 shows two stimuli (vertical meridian is drawn only for reference purposes):
8
image A depicts a scenario in which the best (closest) passing option is the team mate on the left 9
of the meridian; image B depicts the reverse. There were 48 images in total, each presented once;
10
presentation of stimuli was balanced such that the best passing option was equally represented in 11
both left and right hemifields.
12
4.1.2.3. Netball decision-making task stimuli. Thirty-two still images, which had been 13
taken from a pool of 60 first-person perspective shots of competitive netball scenarios, were 14
used; Figure 3 shows one of the images. It was explained to participants that the players in dark 15
grey tops (no bibs) were team mates and that the aim of the task was to identify the best passing 16
option – as previously judged by two international netball coaches and an international netball 17
performance analyst ( x international experience = 15.3 yrs; SD = 4.8 yrs). All images were 18
flipped to form an equivalent set of mirror images, such that each scenario was associated with 19
both a left-located and a right-located best passing option, yielding a total of 64 experimental 20
trials.
21
4.1.2.4. Auditory stimuli. As for Experiment 1, participants heard an auditory cue varying both 22
semantically and spatially, at an SOA of 0 ms. For each task, there was an equal number of trials
23
for which (a) both spatial and semantic components of the cue were valid (i.e., both were 1
designed to orient attention to the correct side; valid-valid
;e.g., a call of “right” in the right ear, 2
when the target was located in the right side of the display); (b) only the spatial component was 3
valid (valid–invalid; e.g., a call of “right” in the left ear, when the target was located in the left 4
side of the display); (c) only the semantic component was valid (invalid–valid; e.g., a call of 5
“right” in the left ear, when the target was located on the right side of the display); and (d) both 6
components were invalid (invalid–invalid; e.g., a call of “right” in the right ear, when the target 7
was located on the left side of the display); hence, the cues were entirely non-predictive, 8
occurring congruently with the target at chance frequency (NB: participants were unaware of the 9
predictive validity of the cues).
10
4.1.3. Procedure.
11
Participants were required to wear earphones throughout the entire protocol. They were 12
verbally informed that each trial would commence as soon as the stimulus appeared and that the 13
auditory cue may or may not relate to the correct response; on-screen instructions reaffirmed 14
this. Each trial was preceded by a fixation cross in the centre of the screen for 500 ms. Displays 15
remained visible until participants made a key press response. No feedback was given in between 16
trials. The order of all trials was randomized. In each experiment, participants performed ten 17
familiarisation trials. They proceeded to the experimental trials after reporting that they 18
understood the task requirements.
19
4.1.4. Data analysis – all tasks.
20
All data were analysed using PASW Statistics (v 18.0, SPSS Inc., Chicago, IL). A two- 21
way MANOVA (semantic component validity x spatial component validity) was conducted; the 22
dependent measures were accuracy and response time.
23
4.2. Results 1
4.2.1. Visual detection task.
2
There was no significant interaction effect. There were main effects of both the semantic 3
component, F (2,40) = 3.99, p = .030, Pillai’s Trace = .17,
p2= .17, and of the spatial 4
component, F (2,40) = 8.62, p = .001, Pillai’s Trace = .30,
p2= .30,. Univariate tests revealed 5
that semantically invalid cues ( x = 894.83 ms; SD = 302.71 ms) elicited slower responses than 6
did valid ones, ( x = 874.18 ms; SD = 278.54 ms), F(1,41) = 6.98, p = .010,
p2= .15, 95% CI = 7
4.86–36.43 ms; as did spatially invalid cues ( x = 898.13 ms; SD = 296.42 ms) relative to valid 8
ones ( x = 870.89 ms; SD = 284.83 ms), F(1,41) = 17.07, p < .001,
p2= .29, 95% CI = 13.92–
9
40.55 ms (see Fig. 4(A)).
10
4.2.2. Visual discrimination task.
11
There was a significant interaction effect of the two cue components, F(2,40) = 5.33, p = 12
.009, Pillai’s Trace = .21. Univariate tests showed that there was an effect on accuracy, F(1,41) = 13
6.40, p = .015,
p2= .14; follow-up tests showed that doubly valid cues ( x = 76.63%; SD = 14
16.19%) elicited more accurate responses than did a cue that was spatially invalid but 15
semantically valid ( x =71.33%; SD = 20.53%), p = .002. This disordinal interaction is depicted 16
in Figure 5(A).
17
There was a main effect of the spatial component, F (2,40) = 5.29, p = .009, Pillai’s Trace 18
= .21,
p2= .21. Univariate tests revealed that spatially valid cues ( x = 74.73%, SD = 17.16%) 19
led to greater accuracy than did those that were invalid ( x = 71.85%, SD = 20.83%), F (1,41) = 20
5.60, p = .023,
p2= .12, 95% CI = 0.40–5.30% (see Fig. 4B). There was no effect of the 21
semantic component.
22
4.2.3. Netball task.
1
There was a significant interaction effect of cue components, F(2,40) = 3.67, p = .034, 2
Pillai’s Trace = .16,
p2= .16. Univariate tests showed that there was an effect on accuracy, 3
F(1,41) = 6.88, p = .012,
p2= .15; follow-up tests revealed that doubly valid cues (M = 75.21%;
4
SD = 13.84%) elicited more accurate responses than did both conditions in which the cue was 5
spatially invalid (semantically invalid cue, x = 63.69%; SD = 12.86%; semantically valid cue, 6
x = 69.79%; SD = 12.73%), p < .002. This ordinal interaction is depicted in Figure 5(B).
7
There were main effects of both the semantic component, F(2,40) = 14.27, p < .001, 8
Pillai’s Trace = .16,
p2= .16, and the spatial component, F(2,40) = 25.66, p < .001, Pillai’s 9
Trace = .56,
p2= .56,. Univariate tests revealed that semantically invalid cues reduced accuracy 10
( x = 69.25%; SD = 12.22%) relative to valid ones ( x = 72.50%; SD = 13.28%), F(1,41) = 5.04, 11
p = .030,
p2= .11, 95% CI = 0.30%–6.20%; they also increased response times ( x = 1544.92 12
ms; SD = 593.07 ms vs. x = 1437.04 ms; SD = 489.30 ms, respectively), F(1,41) = 16.58, p <
13
.001,
p2= .29. Spatially invalid cues (M = 66.74%; SD = 12.80%) also decreased accuracy, 14
F(1,41) = 37.12, p < .001,
p2= .48, 95% CI = 5.50–11.0%; and increased response times (M = 15
1532.79 ms; SD = 560.57 ms vs. x = 1449.17 ms; SD = 521.79 ms), F(1,41) = 12.93, p = .001, 16
p2= .24, 95% CI = 36.35–136.59 ms (see Figs. 4(C) & 4(D)).
17
5. Discussion 18
We conducted two experiments designed to illustrate the impact of spoken cues on 19
participants’ visual attention and decision-making. The findings provide considerable support for 20
our hypotheses, together with some unexpected findings. In Experiment 1, the experimental 21
manipulation was effective and mirrors Salverda and Altmann’s (2011) findings: valid and
22
invalid auditory spoken cues speeded and slowed detection time relative to a control condition, 1
through a shifting of attention. In Experiment 2 we sought to explore this orienting effect in a 2
group of skilled netballers and to examine the effect of its interaction with task demands on 3
decision-making. In a visual detection task, cues that were both semantically and spatially valid 4
speeded target detection – consistent with our predictions and the extant literature (see Wright &
5
Ward, 2008). A wholly unexpected finding was that spatial cues affected participants’ accuracy 6
in the visual discrimination task; and doubly valid cues appeared to be particularly effective in 7
improving performance on this task. In the netball-specific task, both cue types improved the 8
accuracy of decisions made and reduced the time taken to make them, relative to invalid cues;
9
again, whilst the effect on response times was predicted, the effect on accuracy was not. These 10
findings are discussed in more detail below.
11
The pilot study data clearly show that spoken cues affected non-athletes’ target detection 12
speed; notably it deteriorated in the presence of invalid cues and improved in the presence of 13
valid ones. Hence, our chosen manipulation was effective. Given the superior ability of skilled 14
performers to selectively attend to pertinent visual information (Gegenfurtner, et al., 2011;
15
Mann, et al., 2007), the extent to which spoken cues would affect their performance was deemed 16
worthy of examination, to address an existing gap in the sport literature (e.g., Canal-Bruland &
17
Hagemann, 2007; Castiello & Umiltà, 1992; Enns & Richards, 1997; Hagemann, Strauss, &
18
Cañal-Bruland, 2006). The present findings suggest that, contrary to Nougier et al.’s (1989) 19
findings with visual stimuli, the skilled netballers were equally affected by auditory cues in the 20
visual detection task: the effect sizes of the differences in response times between the doubly 21
valid and doubly invalid conditions, for both the non-netballers (Experiment 1) and the skilled
22
netballers (Experiment 2), were identical (Cohen’s d = 0.16). Eye movement data would 1
establish whether this orienting of attention was overt or covert.
2
The high perceptual demands of the visual discrimination task (cf. Santangelo, et al., 3
2007) appeared to compete effectively with the semantic component for participants’ attention, 4
such that this component did not affect task performance; but the fact that visual detection task 5
performance was affected suggests that they were not simply being ignored. So, whilst the word 6
itself might have increased attention to the cued side, it did not affect the decisions made, nor the 7
time taken to make them. The same cannot be said for the spatial component: when this was 8
valid, participants made more accurate judgements than when they were invalid, which was an 9
entirely unpredicted – and serendipitous – finding. Although we might expect that exogenous 10
cues exert more potent effects on attention (Berger, et al., 2005; Jonides, 1981; Yantis & Jonides, 11
1990), the notion that they might affect subsequent decision-making is very novel – even though 12
comparable effects of auditory cues on visual discrimination judgements have been demonstrated 13
for a line bisection task (Sosa, Clarke, & McCourt, 2011). However, it is noteworthy that, even 14
though participants reported that they had guessed much of the time (cf. Masters, et al., 2007), 15
the percentage of correct responses across all trials ( x = 73.29%) was considerably above the 16
chance level. Therefore, it seems as though the perceptual demands of the task might have 17
interacted with the spatial cues in such a way that the effects of invalid, not valid, cues were 18
typically attenuated; this suggests that bottom-up capture by auditory cues can be suppressed by 19
top-down attentional control – but in a way that is explicitly dependent on the perceived veracity 20
of the visual information (cf. Koelewijn, Bronkhorst, & Theeuwes, 2009).
21
In the netball task, a semantically valid cue (e.g., a call of “left” when the correct passing 22
option was located on the left) improved participants’ accuracy and response times relative to an
23
invalid one (see Figures 4(C) & (D)), consistent with Hagemann et al’s (2006) findings, but in 1
contrast to those of Cañal-Bruland (2009). This may be attributed to the ‘priming’ effect (Soto &
2
Humphreys, 2007) of the words: they were readily accessible at the point of making the decision 3
(cf. Tversky & Kahneman, 1973). Nonetheless, it is important to note that this is still a surprising 4
finding, when considering that the cues were entirely non-predictive – i.e., they were valid for 5
only 50% of trials. The link between exogenous orienting of attention and netball task decision 6
accuracy is not only highly novel, but also challenging to explain. However, a comparable effect 7
was observed by Shimojo, Simion, Shimojo, & Scheier (2003), who exogenously manipulated 8
the duration of participants’ gaze at on-screen faces by increasing the duration for which the 9
faces were presented. Longer durations promoted greater overt attention – and ultimately 10
preferences. Hence, it is possible that, in the present data, the reflexive cueing effect of the 11
exogenous cues promoted an increased gaze duration for the cued side, which engendered a 12
preference for one team mate/passing option over another. Again, eye movement data collection 13
would enable us to determine this unequivocally.
14
The varied effects across the discrimination and netball tasks may be interpreted in light 15
of Lavie et al.’s (2004) Load Theory, which was put forward to resolve the early-versus-late 16
selection debate in attention research. Using a series of experiments, Lavie et al. proposed a 17
hybrid of the two approaches, for which two discrete mechanisms exist: when an ongoing task is 18
perceptually demanding, a passive selection mechanism operates to exclude distracters from 19
perceptual processing; and when cognitive load is high (e.g., when WM is under great demand), 20
a more active system seeks to minimise disruptive intrusions, so as to maintain ongoing task 21
performance. However, the ‘monitoring function’ of this system ironically renders it vulnerable 22
to irrelevant distracters. This seems to have occurred in the present study: although the netball
23
task was arguably more cognitively demanding than the discrimination task – participants were 1
required to anticipate, inter alia, implied player movements, potential interceptions, etc. – it did 2
not present the same perceptual challenge and so performance on this task was more prone to 3
auditory cueing effects. Although Load Theory was developed using visual stimuli, it has since 4
been successfully used as a framework for examining the effects of verbal auditory load on 5
selective attention (Dittrich & Stahl, 2012), and so may provide a useful scaffold for further 6
investigations of crossmodal cueing effects in sport.
7
In contradiction to Load Theory (Lavie, et al., 2004), combined visual and auditory cues 8
successfully capture attention under high perceptual loads (Spence & Santangelo, 2009); hence, a 9
fruitful line of enquiry would be to examine the effects of multimodal cueing (i.e., doubly valid 10
visual and auditory cues in combination) on attention and consequent decision-making. To use 11
such cues would more closely replicate the actuality – the bombardment of the senses that occurs 12
in many sporting contexts; investigations in cognitive psychology have largely been confined to 13
examining the impact of cues in one modality on performance in another, most notably the 14
impact of auditory cues on visual task performance (e.g., Koelewijn, et al., 2009). If an arm- 15
waving, hollering team mate was also the ‘best’ passing option, then such a combination of 16
visual and auditory cues would be doubly valid. Research suggests that effects are most 17
pronounced when the two types are matched along one or more dimensions (e.g., low spatial 18
position and low pitch; Ben-Artzi & Marks, 1995) and so the use of auditory tones played at 19
pitches that correspond to visual cue locations should accelerate attention to, and consequently 20
learning from, previously-identified information-rich regions of the visual display (e.g., 21
Hagemann, et al., 2006). The paradigms employed by Hagemann et al. (2006) and Cañal- 22
Bruland (2009) could easily be adapted to comprise multimodal cues.
23
5.1. Conclusions 1
Our data show that not only did auditory capture of attention occur when performing 2
visual detection tasks, but that decision-making in more complex visual tasks was also affected – 3
often to the extent that decision accuracy improved with cue validity. The most notable and 4
novel finding from the present study was the power of spatial cues to exert this effect; to our 5
knowledge, this has not hitherto been demonstrated in a sport setting. In accordance with 6
previous findings and extant theory (Lavie, et al., 2004), it is apparent that a visual task with high 7
perceptual demands may attenuate the effects of spoken cues – a notion which warrants further 8
consideration, given the inherently multimodal and perceptually demanding nature of many team 9
sports.
10
We have established a profound effect of concurrently presented auditory information on 11
visual detection, visual discrimination and decision-making task performance. Given the 12
evidence for the sharing of neural pathways by both visual and auditory attention (Brown, 13
Clarke, & Barry, 2007; Donohue, Roberts, Grent-'t-Jong, & Woldorff, 2011), this is a necessary 14
and timely consideration. Recent discussion of representative task design has centred on the 15
extent to which perception and action are coupled (Dicks, et al., 2009; Kingsley, Russell, &
16
Benton, 2012; Pinder, et al., 2011; Vilar, et al., 2012). However, auditory information is 17
undeniably a ubiquitous environmental constraint in many sporting contexts – moreover, a 18
demonstrably impactful one – and so warrants greater consideration in future investigations of 19
visual perception and attention in sport, in order to strive for greater task representativeness.
20
6. References 1
Abernethy, B., Neal, R. J., & Koning, P. (1994). Visual-Perceptual and Cognitive Differences 2
Between Expert, Intermediate, and Novice Snooker Players. Applied Cognitive 3
Psychology, 8, 185-211. doi: 10.1002/acp.2350080302 4
Ben-Artzi, E., & Marks, L. E. (1995). Visual-auditory interaction in speeded classification: Role 5
of stimulus difference. Perception & Psychophysics, 57, 1151-1162. doi:
6
10.3758/BF03208371 7
Berger, A., Henik, A., & Rafal, R. (2005). Competition Between Endogenous and Exogenous 8
Orienting of Visual Attention. Journal of Experimental Psychology: General, 134, 207- 9
221. doi: 10.1037/0096-3445.134.2.207 10
Cañal-Bruland, R. (2009). Visual cueing in sport-specific decision-making. International 11
Journal of Sport & Exercise Psychology, 7(4), 450-464. doi:
12
10.1080/1612197X.2009.9671919 13
Canal-Bruland, R., & Hagemann, N. (2007). Posner's cueing paradigm with sport-specific 14
stimuli. Journal of Sport & Exercise Psychology, 29, S58-S59. doi:
15
10.1080/1612197X.2009.9671919 16
Castiello, U., & Umiltà, C. (1992). Orienting of attention in volleyball players. International 17
Journal of Sport Psychology, 23, 301-310.
18
Dicks, M., Davids, K., & Button, C. (2009). Representative task designs for the study of 19
perception and action in sport. International Journal of Sport Psychology, 40(4), 506- 20
524.
21
Dittrich, K., & Stahl, C. (2012). Selective impairment of auditory selective attention under 1
concurrent cognitive load. Journal of Experimental Psychology: Human Perception and 2
Performance, 38, 618-627. doi: 10.1037/a0024978 3
Enns, J. T., & Richards, J. C. (1997). Visual attentional orienting in developing hockey players.
4
Journal of Experimental Child Psychology, 64, 255-275. doi: 10.1006/jecp.1996.2348 5
Gegenfurtner, A., Lehtinen, E., & Säljö, R. (2011). Expertise Differences in the Comprehension 6
of Visualizations: a Meta-Analysis of Eye-Tracking Research in Professional Domains.
7
Educational Psychology Review, 23, 523-552. doi: 10.1007/s10648-011-9174-7 8
Hagemann, N., Strauss, B., & Cañal-Bruland, R. (2006). Training Perceptual Skill by Orienting 9
Visual Attention. Journal of Sport & Exercise Psychology, 28, 143-158.
10
Hughes, P. K., Blundell, N. L., & Walters, J. M. (1993). Visual and psychomotor performance of 11
elite, intermediate and novice table tennis competitors. Clinical & Experimental 12
Optometry, 76, 51-60. doi: 10.1111/j.1444-0938.1993.tb05090.x 13
Jonides, J. (1981). Voluntary vs. automatic control over the mind's eye in movement. In J. B.
14
Long & A. D. Baddeley (Eds.), Attention and Performance IX. Hillsdale, NJ: Erlbaum.
15
Kingsley, M., Russell, M., & Benton, D. (2012). Authors' response to letter to the Editor: "The 16
need for 'representative task design' in evaluating efficacy of skills tests in sport: A 17
comment on Russell, Benton and Kingsley (2010)". Journal Of Sports Sciences, 30(16), 18
1731-1733.
19
Koelewijn, T., Bronkhorst, A., & Theeuwes, J. (2009). Auditory and visual capture during 20
focused visual attention. Journal of Experimental Psychology: Human Perception and 21
Performance, 35, 1303-1315. doi: 10.1037/a0013901
22
Lavie, N., Hirst, A., de Fockert, J. W., & Viding, E. (2004). Load Theory of Selective Attention 1
and Cognitive Control. Journal of Experimental Psychology: General, 133, 339-354. doi:
2
10.1037/0096-3445.133.3.339 3
Mann, D. T. Y., Williams, A. M., Ward, P., & Janelle, C. M. (2007). Perceptual-Cognitive 4
Expertise in Sport: A Meta-Analysis. Journal of Sport & Exercise Psychology, 29, 457- 5
478.
6
Masters, R. S. W., van der Kamp, J., & Jackson, R. C. (2007). Imperceptibly Off-Center 7
Goalkeepers Influence Penalty-Kick Direction in Soccer. Psychological Science, 18, 222- 8
223. doi: 10.1111/j.1467-9280.2007.01878.x 9
Nougier, V., Ripoll, H., & Stein, J. F. (1989). Orienting of attention with highly skilled athletes.
10
International Journal of Sport Psychology, 20, 205-223.
11
Pinder, R. A., Davids, K., Renshaw, I., & Araújo, D. (2011). Representative Learning Design 12
and Functionality of Research and Practice in Sport. Journal of Sport & Exercise 13
Psychology, 33(1), 146-155.
14
Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 15
3-25. doi: 10.1080/00335558008248231 16
Posner, M. I., Snyder, C. R., & Davidson, B. J. (1980). Attention and the detection of signals.
17
Journal of Experimental Psychology: General, 109(2), 160-174. doi: 10.1037/0096- 18
3445.109.2.160 19
Salverda, A. P., & Altmann, G. T. M. (2011). Attentional capture of objects referred to by 20
spoken language. Journal of Experimental Psychology: Human Perception and 21
Performance, 37, 1122-1133.
22
Santangelo, V., Olivetti Belardinelli, M., & Spence, C. (2007). The suppression of reflexive 1
visual and auditory orienting when attention is otherwise engaged. Journal of 2
Experimental Psychology: Human Perception and Performance, 33, 137-148. doi:
3
10.1037/0096-1523.33.1.137 4
Shimojo, S., Simion, C., Shimojo, E., & Scheier, C. (2003). Gaze bias both reflects and 5
influences preference. Nature Neuroscience, 6, 1317-1322. doi: 10.1038/nn1150 6
Sosa, Y., Clarke, A. M., & McCourt, M. E. (2011). Hemifield asymmetry in the potency of 7
exogenous auditory and visual cues. Vision Research, 51, 1207-1215. doi:
8
10.1016/j.visres.2011.03.012 9
Soto, D., & Humphreys, G. W. (2007). Automatic guidance of visual attention from verbal 10
working memory. Journal of Experimental Psychology: Human Perception and 11
Performance, 33, 730-737. doi: 10.1037/0096-1523.33.3.730 12
Spence, C. (2001). Crossmodal attentional capture: a controversy resolved? In C. Folk & B.
13
Gibson (Eds.), Attention, distraction and action: multiple perspectives on attentional 14
capture (pp. 231-262). Amsterdam: Elsevier Science BV.
15
Spence, C., & Santangelo, V. (2009). Capturing spatial attention with multisensory cues: A 16
review. Hearing Research, 258, 134-142. doi: 10.1016/j.heares.2009.04.015 17
Theeuwes, J., Kramer, A. F., Hahn, S., & Irwin, D. E. (1998). Our eyes do not always go where 18
we want them to go: Capture of the eyes by new objects. Psychological Science, 9(5), 19
379-385. doi: 10.1111/1467-9280.00071 20
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and 21
probability. Cognitive Psychology, 5, 207-232. doi: 10.1016/0010-0285(73)90033-9
22
Vilar, L., Araújo, D., Davids, K., & Renshaw, I. (2012). The need for 'representative task design' 1
in evaluating efficacy of skills tests in sport: A comment on Russell, Benton and 2
Kingsley (2010). Journal Of Sports Sciences, 30(16), 1727-1730.
3
Ward, P., Williams, A. M., & Loran, D. F. C. (2000). The development of visual function in elite 4
and sub-elite soccer players. International Journal of Sports Vision, 6, 1-11.
5
Williams, A. M., & Grant, A. (1999). Training perceptual skill in sport. International Journal of 6
Sport Psychology, 30, 194-220.
7
Wright, R. D., & Ward, L. M. (2008). Orienting of attention. Oxford: Oxford University Press.
8
Yantis, S., & Jonides, J. (1990). Abrupt visual onsets and selective attention: Voluntary versus 9
automatic allocation. Journal of Experimental Psychology: Human Perception and 10
Performance, 16, 121-134. doi: 10.1037/0096-1523.16.1.121 11
12
13
7. Figures 1
2
Figure 1. Visual detection task – sample stimulus
3
1
Figure 2. Visual discrimination task – two sample stimuli
2
1
Figure 3. Netball task – sample stimulus 2
3
4
*** * *
A Visual Detection Task B Visual Discrimination Task
C Netball Task - Accuracy D Netball Task – Response Time
*** * ** ***
Spatial component
Invalid Valid
Spatial component
Invalid Valid Invalid Valid Semantic component
Spatial component
Invalid Valid Invalid Valid
Semantic component Spatial component
Invalid Valid Invalid Valid Semantic component
